Historical changes and projected trends of extreme climate events in Xinjiang, China

2022 ◽  
Author(s):  
Jingyun Guan ◽  
Junqiang Yao ◽  
Moyan Li ◽  
Dong Li ◽  
Jianghua Zheng
Keyword(s):  
Historical Changes ◽  
Extreme Climate Events ◽  
Extreme Climate ◽  
Climate Events

Can animal habitat use patterns influence their vulnerability to extreme climate events? An estuarine sportfish case study

2017 ◽  
Vol 23 (10) ◽  
pp. 4045-4057 ◽  
Author(s):  
Ross E. Boucek ◽  
Michael R. Heithaus ◽  
Rolando Santos ◽  
Philip Stevens ◽  
Jennifer S. Rehage
Keyword(s):  
Habitat Use ◽  
Extreme Climate Events ◽  
Use Patterns ◽  
Extreme Climate ◽  
Climate Events ◽  
Animal Habitat

Spatiotemporal variations of extreme climate events in Northeast China during 1960–2014

2019 ◽  
Vol 96 ◽  
pp. 669-683 ◽  
Author(s):  
Enliang Guo ◽  
Jiquan Zhang ◽  
Yongfang Wang ◽  
Lai Quan ◽  
Rongju Zhang ◽  
...  
Keyword(s):  
Northeast China ◽  
Spatiotemporal Variations ◽  
Extreme Climate Events ◽  
Extreme Climate ◽  
Climate Events

scholarly journals Effects of Extreme Climate Events on Tea (Camellia sinensis) Functional Quality Validate Indigenous Farmer Knowledge and Sensory Preferences in Tropical China

PLoS ONE ◽  
2014 ◽  
Vol 9 (10) ◽  
pp. e109126 ◽  
Author(s):  
Selena Ahmed ◽  
John Richard Stepp ◽  
Colin Orians ◽  
Timothy Griffin ◽  
Corene Matyas ◽  
...  
Keyword(s):  
Camellia Sinensis ◽  
Farmer Knowledge ◽  
Extreme Climate Events ◽  
Extreme Climate ◽  
Functional Quality ◽  
Tropical China ◽  
Climate Events

scholarly journals Temporal clustering of extreme climate events drives a regime shift in rocky intertidal biofilms

Ecology ◽  
2019 ◽  
Vol 100 (2) ◽  
pp. e02578 ◽  
Author(s):  
Martina Dal Bello ◽  
Luca Rindi ◽  
Lisandro Benedetti‐Cecchi
Keyword(s):  
Regime Shift ◽  
Rocky Intertidal ◽  
Extreme Climate Events ◽  
Temporal Clustering ◽  
Extreme Climate ◽  
Climate Events

scholarly journals Impact of recent climate extremes on mosquito-borne disease transmission in Kenya

2021 ◽  
Vol 15 (3) ◽  
pp. e0009182
Author(s):  
Cameron Nosrat ◽  
Jonathan Altamirano ◽  
Assaf Anyamba ◽  
Jamie M. Caldwell ◽  
Richard Damoah ◽  
...  
Keyword(s):  
Climate Change ◽  
Disease Transmission ◽  
Enzyme Linked Immunosorbent Assay ◽  
Mosquito Abundance ◽  
Targeted Interventions ◽  
Extreme Climate Events ◽  
Extreme Climate ◽  
Recent Climate ◽  
Climate Events ◽  
The Impact

Climate change and variability influence temperature and rainfall, which impact vector abundance and the dynamics of vector-borne disease transmission. Climate change is projected to increase the frequency and intensity of extreme climate events. Mosquito-borne diseases, such as dengue fever, are primarily transmitted by Aedes aegypti mosquitoes. Freshwater availability and temperature affect dengue vector populations via a variety of biological processes and thus influence the ability of mosquitoes to effectively transmit disease. However, the effect of droughts, floods, heat waves, and cold waves is not well understood. Using vector, climate, and dengue disease data collected between 2013 and 2019 in Kenya, this retrospective cohort study aims to elucidate the impact of extreme rainfall and temperature on mosquito abundance and the risk of arboviral infections. To define extreme periods of rainfall and land surface temperature (LST), we calculated monthly anomalies as deviations from long-term means (1983–2019 for rainfall, 2000–2019 for LST) across four study locations in Kenya. We classified extreme climate events as the upper and lower 10% of these calculated LST or rainfall deviations. Monthly Ae. aegypti abundance was recorded in Kenya using four trapping methods. Blood samples were also collected from children with febrile illness presenting to four field sites and tested for dengue virus using an IgG enzyme-linked immunosorbent assay (ELISA) and polymerase chain reaction (PCR). We found that mosquito eggs and adults were significantly more abundant one month following an abnormally wet month. The relationship between mosquito abundance and dengue risk follows a non-linear association. Our findings suggest that early warnings and targeted interventions during periods of abnormal rainfall and temperature, especially flooding, can potentially contribute to reductions in risk of viral transmission.

scholarly journals Quantifying the influence of global warming on unprecedented extreme climate events

2017 ◽  
Vol 114 (19) ◽  
pp. 4881-4886 ◽  
Author(s):  
Noah S. Diffenbaugh ◽  
Deepti Singh ◽  
Justin S. Mankin ◽  
Daniel E. Horton ◽  
Daniel L. Swain ◽  
...  
Keyword(s):  
Global Warming ◽  
Climate Model ◽  
Arctic Sea Ice ◽  
Climate Forcing ◽  
Sea Ice Extent ◽  
Extreme Climate Events ◽  
Atmospheric Circulation Patterns ◽  
Extreme Climate ◽  
Substantial Progress ◽  
Climate Events

Efforts to understand the influence of historical global warming on individual extreme climate events have increased over the past decade. However, despite substantial progress, events that are unprecedented in the local observational record remain a persistent challenge. Leveraging observations and a large climate model ensemble, we quantify uncertainty in the influence of global warming on the severity and probability of the historically hottest month, hottest day, driest year, and wettest 5-d period for different areas of the globe. We find that historical warming has increased the severity and probability of the hottest month and hottest day of the year at >80% of the available observational area. Our framework also suggests that the historical climate forcing has increased the probability of the driest year and wettest 5-d period at 57% and 41% of the observed area, respectively, although we note important caveats. For the most protracted hot and dry events, the strongest and most widespread contributions of anthropogenic climate forcing occur in the tropics, including increases in probability of at least a factor of 4 for the hottest month and at least a factor of 2 for the driest year. We also demonstrate the ability of our framework to systematically evaluate the role of dynamic and thermodynamic factors such as atmospheric circulation patterns and atmospheric water vapor, and find extremely high statistical confidence that anthropogenic forcing increased the probability of record-low Arctic sea ice extent.

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